CarePredict

CarePredict is the wearable AI for elderly activity, fall, and behavior-pattern monitoring. Founded in 2013 in Plantation, Florida, CarePredict has developed a wrist-worn device (Tempo) that continuously captures accelerometer data, location data within the facility, and audio context. Machine learning models on the continuous data detect routine changes that predict urinary tract infections, falls, and depression days-to-weeks before human caregivers would notice the symptoms. CarePredict serves skilled nursing facilities, assisted living, memory care, and increasingly home settings. The platform's value proposition is shifting elderly care from reactive ("she fell — let's respond") to predictive ("her gait pattern has changed over the past week — increased UTI risk"). The Tempo wearable is comfortable enough for most elderly residents to wear continuously with battery life of several days. Activity pattern recognition is the platform's core ML capability — continuous accelerometer + location data is processed into per-resident activity patterns, personalized to each resident and updated daily. UTI risk prediction is the most-published outcome — urinary tract infections are the leading cause of acute hospitalization for elderly residents, and CarePredict's models flag pattern shifts that historically have predicted UTI 3-7 days before clinical symptoms emerge. Fall detection plus fall-risk prediction catches both real-time falls and gait-speed slowdowns that predict future falls. For memory-care residents, the indoor-location tracking flags wandering patterns and exit-seeking behavior. The family communication app sends daily summaries to family members, strengthening trust and reducing anxiety calls.